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Remote Data Scientist Fraud Jobs in Michigan (NOW HIRING)

Bright Vision Technologies

AI Data Engineer

Troy, MI · Remote

$100K/mo

AI Data Engineer - Remote Bright Vision Technologies is a technology consulting and software ... Bachelor's or Master's degree in Computer Science or a related field. * Six or more years of data ...

Toyota

Sr. Principal Scientist - R&D

Ann Arbor, MI · On-site +1

Must have a PhD in Engineering, Computer Science, Data Science, Physical Sciences, Business ... Remote work on Fridays may be permitted based on project priorities and business requirements ...

Stryker

Senior Staff Data Engineer

Portage, MI · On-site +1

$153K - $255K/yr

Remote Join a team focused on building scalable, enterprise-grade data platforms that support ... Bachelor's degree in Computer Science, Data Analytics, Mathematics, Statistics, Data Science, or a ...

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Remote Data Scientist Fraud information

What does a remote data scientist fraud do?

A Remote Data Scientist Fraud specializes in detecting and preventing fraudulent activities using data analysis and machine learning techniques. They work from a remote location to gather, analyze, and interpret large datasets to identify suspicious patterns and anomalies. Their role often involves building predictive models, collaborating with engineering and cybersecurity teams, and continuously improving fraud detection systems. By leveraging statistical tools and algorithms, they help organizations minimize financial losses and enhance security.

What are the key skills and qualifications needed to thrive as a remote data scientist fraud?

To thrive as a Remote Data Scientist in Fraud Detection, you need strong analytical skills, a solid background in statistics or computer science, and experience with machine learning, often supported by an advanced degree. Familiarity with tools such as Python, R, SQL, and fraud detection platforms like SAS or Hadoop, as well as knowledge of data visualization and cloud technologies, is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for interpreting complex data and collaborating remotely across teams. These skills ensure accurate fraud identification, efficient risk mitigation, and effective cross-functional teamwork in dynamic and distributed environments.

How does a remote data scientist fraud typically collaborate with cross-functional teams?

As a Remote Data Scientist focused on fraud detection, you'll regularly collaborate with engineers, product managers, and risk analysts to design and implement effective fraud prevention solutions. Communication is often facilitated through virtual meetings, collaborative platforms, and shared documentation. You'll be expected to explain complex models and analytical findings in clear, actionable terms to both technical and non-technical stakeholders, ensuring everyone understands the impact of your work. Strong teamwork and proactive updates are essential for keeping projects aligned and ensuring the solutions stay relevant to evolving fraud trends.

What are popular job titles related to Remote Data Scientist Fraud jobs in Michigan?

For Remote Data Scientist Fraud jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Remote Data Scientist Fraud jobs in Michigan look for?

The top searched job categories for Remote Data Scientist Fraud jobs in Michigan are:

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Cities in Michigan with the most Remote Data Scientist Fraud job openings:

Remote Data Scientist Fraud jobs near you

AI Training Specialist - Life Sciences

micro1 AI

Lansing, MI • Remote

$90 - $120/hr

Part-time

Posted 21 days ago

Job description

Role Title: Bioinformatics Scientist


Role Type: Contractor


Location: Remote


micro1 is engaging Bioinformatics Scientists to contribute their specialized expertise to a customer's innovative project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Analyze complex datasets related to medicinal chemistry using advanced bioinformatics methodologies.
  2. Provide detailed scientific input and content to support the development and training of AI models.
  3. Curate, annotate, and validate datasets relevant to drug discovery and molecular analysis.
  4. Evaluate and synthesize findings from biological, chemical, and clinical data sources.
  5. Offer subject matter expertise on experimental design and data interpretation within medicinal chemistry.
  6. Assess AI-generated outputs for scientific accuracy, relevance, and reliability.
  7. Deliver comprehensive written feedback and actionable recommendations for model improvement.


Preferred Qualifications

  1. Advanced degree (e.g., PhD or MSc) in Bioinformatics, Computational Biology, Medicinal Chemistry, or a related discipline.
  2. In-depth knowledge of medicinal chemistry concepts, including structure-activity relationships and drug design principles.
  3. Demonstrated experience in handling and interpreting large-scale omics or cheminformatics datasets.
  4. Familiarity with software tools, databases, and programming languages commonly used in bioinformatics (e.g., Python, R, RDKit, KNIME).
  5. Strong scientific communication skills, with the ability to clearly articulate complex ideas and technical concepts.
  6. Proven track record of contributing to research projects at the intersection of biology, chemistry, and data science.
  7. Experience collaborating in multidisciplinary or remote project environments is advantageous.

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